Most of my time lately has gone into Flippd, its successor, which we recently soft-launched. We’ve also released a tech demo that uses custom computer-vision models to identify a pinball machine from a photo and extract the player’s score.

You can try it here: https://flippd.gg/scan

Our locations are sourced from Pinball Map; scores can be tagged with locations which allows us to maintain leaderboards for specific machines (in addition to global/social/event leaderboards).

> Javascript :)

Pass

For fun, I just implemented a finite-state machine for a videogame I'm working on in Rust. It's used to swap out sprite animations depending on the state of its parent entity. I'm glad to be solving problems I'd never come across in my normal line of work.

    Location: Birmingham, AL
    Remote: Yes
    Willing to relocate: No
    Technologies: Node, Express, React, React Native, GraphQL, Typescript, MongoDB, SQL, Docker
    Résumé/CV: https://www.linkedin.com/in/brendanturner/
    Email: hnjobs@foglet.io
    Hobby Project: https://www.patreon.com/pindigo

M.S. in Data Science - Dec '21

I've spent the last 6 years planning and building HIPAA-compliant web applications in Javascript.

As a hobbyist homelabber and the sole technical developer of a hobby app for 8k users, I also have experience with mobile app development, network engineering, sysadmin, and devops.

The preprocessing to increase DPI to 300 did not help when I tried Tesseract, unfortunately. It’s hard to achieve a good contrast between the numbers and the backdrop